A colorimetric analysis is a technique that measures the properties of the substance using color changes in chemical or biochemical analysis. It is vital in analysing biological, medical, and environmental samples in many fields, such as the food, medicine, cosmetics, and paint industries. Colorimetric analysis requires correct measurement and calibration techniques to obtain accurate results.
At the core of our growing societies, energy supply stands as one of the major concerns today, and it will be an inevitable challenge for our near future. As the nations are looking to find solutions for the transition from fossil fuels – depleting at a high rate – to alternative energy sources, solar energy through PV cells is getting attention as an affordable and easily implemented option especially for power supply in commercial and residential buildings.
Hand gesture-based systems are one of the most effective technological advances. Surface electromyography (sEMG) is utilized as a popular input data for gesture classification with elevated accuracy and advanced control capability. In this thesis, which is based on the classification performance of Hilbert-Huang spectrum (HHS) images obtained from Hilbert Huang Transform (HHT) of the sEMG of the gestures, an evaluation of the results of artificial intelligence (AI) methods on hand gesture classification using HHS image is presented.
6698 sayılı Kişisel Verilerin Korunması Kanunu kapsamında yükümlülüklerimiz ve çerez politikamız hakkında bilgi sahibi olmak için alttaki bağlantıyı kullanabilirsiniz.